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The Cat's Eye Effect target recognition Method Based on Visual Attention

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Chinese Journal of Electronics 2019年第5期28卷 1080-1086页

作者： WANG Xingbin ZHANG Jun WANG Shuaihui State Key Laboratory of Information Security Institute of Information Engineering Chinese Academy of Science University of Chinese Academy of Sciences Hubei University of Arts and Science Changchun Institute of Optics Fine Mechanics and Physics Chinese Academy of Sciences

The Cat’s eye effect target recognition method based on visual attention(CTRVA) is *** difference image can be processed by a designed second-directional derivative filter at eight directional channels. Morphological method is employed to deal with the filtered image in all directions, which ensures that target can be easily distinguished from background. The salient maps for each channel where the potential targets exist are calculated through the spectral residual approach,and the "target-saliency" map is computed by a designed saliency fusing method. The coarse detection is performed by the adaptive threshold to extract candidate targets from the "target-saliency" map. The real target region is identified by the characteristics of the cat’s eye effect target. Experimental results show that the proposed method is efficient and has an outstanding performance for cat’s eye effect target detection.

关键词： Cat’s eye effect target recognition method based on visual attention(CTRVA) target recognition Saliency map

UWB radar target recognition based on time-domain bispectrum

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Journal of Systems Engineering and Electronics 2006年第2期17卷 274-278页

作者： Liu Donghong Zhang Yongshun Chen Zhijie Cheng Junbin The Missile Inst. Air Force Engineering Univ. Sanyuan 713800 P.R. China The Radar and EW Inst. Equipment Academy of Air Force Beijing 100085 P.R. China Nanjing Univ. of Aeronautics and Astronautics Nanjing 210016 P.R. China

Complex targets are irradiated by UWB radar, not only the mirror scattering echoes but also the multiscattering interacting echoes are included in target echoes. These two echoes can not be distinguished by classical frequency spectrum and power spectrurm. Time-domain bispectrum features of UWB radar signals that mingled with noise are analyzed, then processing this kind of signal using the method of time-domain bispectrum is experimented. At last, some UW-B radar returns with different signal noise ratio are simulated using the method of time-domain bispectrum Theoretical analysis and the results of simulation show that the method of extraction partial features of UWB radar targets based on time-domain bispectrum is good, and target classification and recognition can be implemented using those features.

关键词： UWB Radar target recognition bispectrum higher-order spectra.

Research on target recognition and mobile job control of humanoid robot based on KM34Z256 for industrial applications

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International Journal of Intelligent Computing and Cybernetics 2021年第2期14卷 302-318页

作者： Dunhai Wang Amit Sharma Xi’an International University XianChinaand Jaypee University of Information Technology SolanIndia

Purpose-Humanoid robot has similar shape and action characteristics as humans,and it can complete some basic tasks instead of humans without changing the human environment,which makes humanoid robot become the best structure and help form for robot to provide services for human ***/methodology/approach-The mobile operation control of humanoid robot is generated by the walking movement of humanoid robot’s feet,and the robot’s hand and arm complete grasping and other operations ***-On the basis of humanoid robot,the integrated system of software and hardware based on the KM34Z256 humanoid robot is described first,and a series of kinematics discussion on its mobile operation is carried ***/value-The research based on this project shows that the target recognition and positioning method is not only accurate and of high energy but also can realize the mobile operation of humanoid robot.

关键词： Humanoid robot target recognition Mobile operation Industrial automation

LLE-BASED CLASSIFICATION ALGORITHM FOR MMW RADAR target recognition

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Journal of Electronics(China) 2010年第1期27卷 139-144页

作者： Luo Lei Li Yuehua Luan Yinghong School of Electronic Engineering and Optoelectronic Technology Nanjing University of Science and Technology Nanjing 210094 China

In this paper,a new multiclass classification algorithm is proposed based on the idea of Locally Linear Embedding(LLE),to avoid the defect of traditional manifold learning algorithms,which can not deal with new sample *** algorithm defines an error as a criterion by computing a sample's reconstruction weight using ***,the existence and characteristics of low dimensional manifold in range-profile time-frequency information are explored using manifold learning algorithm,aiming at the problem of target recognition about high range resolution MilliMeter-Wave(MMW) *** new algorithm is applied to radar target *** experiment results show the algorithm is *** with other classification algorithms,our method improves the recognition precision and the result is not sensitive to input parameters.

关键词： Manifold learning Locally Linear Embedding(LLE) Multi-class classification MilliMeter-Wave(MMW) target recognition

A New Effective Method for Ship target recognition

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Journal of Systems Engineering and Electronics 1990年第1期1卷 55-63页

作者： Guo Guirong, Yu Wenxian and Hu Bufa(Electrical Engineering Lab, Changsha Institute of Technology, Hunan) Electrical Engineering Lab Changsha Institute of Technology Hunan

In this paper, the problem of reliable automatic target recognition from incoherent radar returns is discussed and a new method for ship target recognition is proposed. Based on this method, an experimental system for ship target recognition is implemented. The results obtained from the theoretical and experimental study indicate that a high reliability of recognition can be achieved by using the designed recognition system. An average success rate of more than 90% is reached for 8 classes of ships.

关键词： target recognition recognition system Feature extraction.

A New Method for target recognition

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The Journal of China Universities of Posts and Telecommunications 2004年第3期11卷 87-90页

作者： LUJian-dong Science and Technology Department Xi'anInstituteofPostsandTelecommunicationsXi'an710061P.R.China

A reasonable explanation is given for possibility distribution descriptor that defined by Hall and Kandel and used in target recognition. Based on this explanation, possibility distribution entropy is defined. Some properties of possibility distribution entropy are discussed and a experiment for recognition of two fighters is shown.

关键词： fuzzy set possibility distribution target recognition

target recognition and Tracking Based on Scale Adaptive Kernel Correlation Filter for Dynamic Perspective of Robots

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Target Recognition and Tracking Based on Scale Adaptive Kern...

target recognition Method for Carrier Aircraft Fleet based on Improved D-S Evidence Theory

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作者： Yusheng Wang Jialong Xie Hongye Zhai Botao Zhang Chaoliang Zhong School of Automation Hangzhou Dianzi University Institute of Intelligent Systems and Control Zhejiang University

An autonomous target recognition and tracking method based on improved Kernel Correlation Filter(KCF) is proposed to deal with camera jitter and changing environments in dynamic perspective for mobile robots. Firstly, the Speeded Up Robust Features detection algorithm is combined with Random Sample Consensus to recognize targets and mark target *** then, KCF is used for rough tracking of the above target areas. Meanwhile, the target re-identification strategy is applied to update the tracking data in real time to solve the problem that the scale of KCF tracking box is too inflexible for accurate ***, tests are carried out not only indoors but also outdoors. The experimental results show that the proposed method can obviously enhance the stability and accuracy of dynamic perspective. Its accuracy is higher than SIFT and KAZE when the camera moves rapidly, and it has better real-time performance and tracking accuracy than KCF and MIL.

关键词： Robot vision Dynamic perspective KCF target recognition target tracking

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Target Recognition Method for Carrier Aircraft Fleet based o...

New Algorithm for Image target recognition Based on Fractal Feature Fusion

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作者： Lifan Sun Jie Zou Zhe Yang School of Information Engineering Henan University of Science and Technology Technology on Electro-optic Control Laboratory

In modern naval warfare,the battlefield environment is extremely complex and *** inaccuracy of information obtained through various radar,ESM,photoelectric,and other detection equipment leads to a high degree of conflict in *** way to effectively integrate this information and accurately identify the enemy targets is the key to victory in *** serve the matter,this paper proposes a carrier aircraft fleet target recognition method based on improved D-S evidence ***,the probability assignment of sensor evidence is transformed by an improved probability assignment *** the transformation of probability is done,and appropriate evidence of the high degree of conflict is collected,the appropriate conflict coefficient is used to calculatethe degree of evidence ***,the target recognition results are obtained through the fusion of the improved evidence theory *** simulation example demonstrates that the method proposed in this paper can effectively solve the conflict problem in target recognition and achieve high-quality evidence combination results to obtain high-speed identification targets,which can be widely used in all kinds of decisions.

关键词： target recognition multi-sensor evidence theory decision fusion

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Journal of Beijing Institute of Technology 2002年第4期11卷 342-345页

作者：潘秀琴侯朝桢苏利敏北京理工大学自动控制系北京100081

By combining fractal theory with D-S evidence theory, an algorithm based on the fusion of multi-fractal features is presented. Fractal features are extracted, and basic probability assignment function is designed. Comparison and simulation are performed on the new algorithm, the old algorithm based on single feature and the algorithm based on neural network. Results of the comparison and simulation illustrate that the new algorithm is feasible and valid.

关键词： fractal feature fusion target recognition